A deficient immune response to SARS-CoV-2 in the nasopharynx is associated with severe COVID-19 pneumonia.

OBJECTIVES: We analyzed the expression of inflammatory and antiviral genes in the nasopharynx of SARS-CoV-2 infected patients and their association with the severity of COVID-19 pneumonia. METHODS: We conducted a cross-sectional study on 223 SARS-CoV-2 infected patients. Clinical data were collected from medical records, and nasopharyngeal samples were collected in the first 24 hours after admission to the emergency room. The gene expression of eight proinflammatory/antiviral genes (plasminogen activator urokinase receptor [PLAUR], interleukin [IL]-6, IL-8, interferon [IFN]-ß, IFN-stimulated gene 15 [ISG15], retinoic acid-inducible gene I [RIG-I], C-C motif ligand 5 [CCL5], and chemokine C-X-C motif ligand 10 [CXCL10]) were quantified by real-time polymerase chain reaction. Outcome variables were: (i) pneumonia; (ii) severe pneumonia or acute respiratory distress syndrome. Statistical analysis was performed using multivariate logistic regression analyses. RESULTS: We enrolled 84 mild, 88 moderate, and 51 severe/critical cases. High expression of PLAUR (adjusted odds ratio [aOR] = 1.25; P = 0.032, risk factor) and low expression of CXCL10 (aOR = 0.89; P = 0.048, protective factor) were associated with pneumonia. Furthermore, lower values of ISG15 (aOR = 0.88, P = 0.021), RIG-I (aOR = 0.87, P = 0.034), CCL5 (aOR = 0.73, P <0.001), and CXCL10 (aOR = 0.84, P = 0.002) were risk factors for severe pneumonia/acute respiratory distress syndrome. CONCLUSION: An unbalanced early innate immune response to SARS-CoV-2 in the nasopharynx, characterized by high expression of PLAUR and low expression of antiviral genes (ISG15 and RIG-I), and chemokines (CCL5 and CXCL10), was associated with COVID-19 severity.

Inference on a Multi-Patched Epidemic Model with Partial Mobility, Residency and Demography: The Case of 2020 COVID-19 Outbreak in Hermosillo, Mexico (preprint)

Most studies modelling population mobility and the spread of infectious diseases, particularly using meta-population-multi-patched models, tend to focus on theoretical properties and numerical simulations of such models. There is relatively scanty literature published on fit, inference and uncertainty quantification on epidemic models with population mobility. In this research, we have used three estimation techniques to solve an inverse problem and quantify its uncertainty on a human mobility-based multi-patched epidemic model, using mobile phone sensing data and COVID-19 confirmed positive cases in Hermosillo, Mexico. First, we have utilized a Brownian bridge model using mobile phone GPS data to estimate residence and mobility parameters of the epidemic model. In the second step, we have estimated the optimal model epidemiological parameters by deterministically inverting the model using a Darwinian inspired evolutionary algorithm (EA) known as the genetic algorithm (GA). The third part of the analysis involves performing inference and uncertainty quantification on the epidemic model using two Bayesian Monte Carlo sampling methods: t-walk and Hamiltonian Monte Carlo (HMC). The results show that the estimated model parameters and incidence adequately fit the observed daily COVID-19 incidence in Hermosillo. Moreover, the estimated parameters from HMC result into large credible intervals, improving their coverage for the observed and predicted daily incidences. We also observe improved predictions when using multi-patch model with mobility against the single-patch model.

National data linkage assessment of live births and deaths in Mexico: Estimating under-five mortality rate ratios for vulnerable newborns and trends from 2008 to 2019.

BACKGROUND: Linked datasets that enable longitudinal assessments are scarce in low and middle-income countries. OBJECTIVES: We aimed to assess the linkage of administrative databases of live births and under-five child deaths to explore mortality and trends for preterm, small (SGA) and large for gestational age (LGA) in Mexico. METHODS: We linked individual-level datasets collected by National statistics from 2008 to 2019. Linkage was performed based on agreement on birthday, sex, residential address. We used the Centre for Data and Knowledge Integration for Health software to identify the best candidate pairs based on similarity. Accuracy was assessed by calculating the area under the receiver operating characteristic curve. We evaluated completeness by comparing the number of linked records with reported deaths. We described the percentage of linked records by baseline characteristics to identify potential bias. Using the linked dataset, we calculated mortality rate ratios (RR) in neonatal, infants, and children under-five according to gestational age, birthweight, and size. RESULTS: For the period 2008-2019, a total of 24,955,172 live births and 321,165 under-five deaths were available for linkage. We excluded 1,539,046 records (6.2%) with missing or implausible values. We succesfully linked 231,765 deaths (72.2%: range 57.1% in 2009 and 84.3% in 2011). The rate of neonatal mortality was higher for preterm compared with term (RR 3.83, 95% confidence interval, [CI] 3.78, 3.88) and for SGA compared with appropriate for gestational age (AGA) (RR 1.22 95% CI, 1.19, 1.24). Births at <28 weeks had the highest mortality (RR 35.92, 95% CI, 34.97, 36.88). LGA had no additional risk vs AGA among children under five (RR 0.92, 95% CI, 0.90, 0.93). CONCLUSIONS: We demonstrated the utility of linked data to understand neonatal vulnerability and child mortality. We created a linked dataset that would be a valuable resource for future population-based research.

Effect of viral storm in patients admitted to intensive care units with severe COVID-19 in Spain: a multicentre, prospective, cohort study

Background The contribution of the virus to the pathogenesis of severe COVID-19 is still unclear. We aimed to evaluate associations between viral RNA load in plasma and host response, complications, and deaths in critically ill patients with COVID-19. Methods We did a prospective cohort study across 23 hospitals in Spain. We included patients aged 18 years or older with laboratory-confirmed SARS-CoV-2 infection who were admitted to an intensive care unit between March 16, 2020, and Feb 27, 2021. RNA of the SARS-CoV-2 nucleocapsid region 1 (N1) was quantified in plasma samples collected from patients in the first 48 h following admission, using digital PCR. Patients were grouped on the basis of N1 quantity: VIR-N1-Zero (<1 N1 copies per mL), VIR-N1-Low (1–2747 N1 copies per mL), and VIR-N1-Storm (>2747 N1 copies per mL). The primary outcome was all-cause death within 90 days after admission. We evaluated odds ratios (ORs) for the primary outcome between groups using a logistic regression analysis. Findings 1068 patients met the inclusion criteria, of whom 117 had insufficient plasma samples and 115 had key information missing. 836 patients were included in the analysis, of whom 403 (48%) were in the VIR-N1-Low group, 283 (34%) were in the VIR-N1-Storm group, and 150 (18%) were in the VIR-N1-Zero group. Overall, patients in the VIR-N1-Storm group had the most severe disease: 266 (94%) of 283 patients received invasive mechanical ventilation (IMV), 116 (41%) developed acute kidney injury, 180 (65%) had secondary infections, and 148 (52%) died within 90 days. Patients in the VIR-N1-Zero group had the least severe disease: 81 (54%) of 150 received IMV, 34 (23%) developed acute kidney injury, 47 (32%) had secondary infections, and 26 (17%) died within 90 days (OR for death 0·30, 95% CI 0·16–0·55;p<0·0001, compared with the VIR-N1-Storm group). 106 (26%) of 403 patients in the VIR-N1-Low group died within 90 days (OR for death 0·39, 95% CI 0·26–0·57;p<0·0001, compared with the VIR-N1-Storm group). Interpretation The presence of a so-called viral storm is associated with increased all-cause death in patients admitted to the intensive care unit with severe COVID-19. Preventing this viral storm could help to reduce poor outcomes. Viral storm could be an enrichment marker for treatment with antivirals or purification devices to remove viral components from the blood. Funding Instituto de Salud Carlos III, Canadian Institutes of Health Research, Li Ka-Shing Foundation, Research Nova Scotia, and European Society of Clinical Microbiology and Infectious Diseases. Translation For the Spanish translation of the see Supplementary Materials section.

Interleukin-6 in SARS-CoV2 risk stratification

Introduction: Since the emergence of COVID19, a broad spectrum of presentation has been described, from the absence of symptoms to critical illness. Some studies show that increased levels of interleukin-6 (IL-6) are correlated with increased mortality and disease severity. Objective(s): To establish the value of IL-6 as an early predictor of severity in SARS-CoV2 infection. Method(s): Prospective study with IL-6 assay as part of the initial study of patients with SARS-CoV2 infection, between 20/10/2021 and 31/01/2022. Two groups were created (I: without hospitalization;II: with hospitalization). Exclusion criteria: chronic respiratory disease, rheumatologic disease and/or inflammatory bowel disease;time between dosing and hospitalization >=72h. Statistics (SPSS v28): Mann Whitney test, AUROC, Spearman correlation. Result(s): Sample of 117 patients (after excluding 10). Group I: 80 patients, 38 (47.5%) were male;mean age of 46.40 +/- 18.85 years old (18-88). Group II: 37 patients, 24 (64.9%) were male;mean age of 72.35 +/- 15.39 years old (29-96). Mean hospital stay of 19.49 +/- 17.02 days;9 (24.3%) were admitted to the ICU. Significantly higher IL-6 values in group II (p<0.001), showing good discriminating power regarding the probability of hospitalization (AUC=0.888;p<0.001) and a statistically significant (p=0.02) positive correlation (0.380) with the length of stay. The optimal cut-off value of IL-6 to establish the need for hospitalization, in our sample, was 12.4 pg/mL (Sensitivity: 97%;Specificity: 69%;Youden index: 0.66). Conclusion(s): IL-6 levels were significantly higher in patients requiring hospitalization and correlated with length of hospital stay. Larger studies are needed to validate its use in risk stratification.

Impact of COVID-19 pandemic on the PREDIMED-Plus randomized clinical trial: Effects on the interventions, participants follow-up, and adiposity.

Background: The COVID-19 pandemic has affected the implementation of most ongoing clinical trials worldwide including the PREDIMED-Plus study. The PREDIMED-Plus is an ongoing, multicenter, controlled intervention trial, aimed at weight-loss and cardiovascular disease prevention, in which participants were randomized (1:1 ratio) to an intervention group (energy-reduced Mediterranean diet, promotion of physical activity, and behavioral support) or to a control group (Mediterranean diet with usual care advice). When the pandemic began, the trial was in the midst of the planned intervention. The objective of this report was to examine the effects of the pandemic on the delivery of the intervention and to describe the strategies established to mitigate the possible adverse effects of the pandemic lockdown on data collection and adiposity. Methods: We assessed the integrity of the PREDIMED-Plus trial during 5 identified periods of the COVID-19 pandemic determined according to restrictions dictated by the Spanish government authorities. A standardized questionnaire was delivered to each of the 23 PREDIMED-Plus recruiting centers to collected data regarding the trial integrity. The effect of the restrictions on intervention components (diet, physical activity) was evaluated with data obtained in the three identified lockdown phases: pre lockdown, lockdown proper, and post lockdown. Results: During the lockdown (March/2020-June/2021), 4,612 participants (48% women, mean age 65y) attended pre-specified yearly follow-up visits to receive lifestyle recommendations and obtain adiposity measures. The overall mean (SD) of the proportions reported by each center showed that 40.4% (25.4) participants had in-person visits, 39.8% (18.2) participants were contacted by telephone and 35% (26.3) by electronic means. Participants' follow-up and data collection rates increased across lockdown periods (from ≈10% at onset to ≈80% at the end). Compared to pre-lockdown, waist circumference increased during (0.75 cm [95% CI: 0.60-0.91]) and after (0.72 cm [95% CI: 0.56-0.89]) lockdown. Body weight did not change during lockdown (0.01 kg [95% CI: -0.10 to 0.13) and decreased after lockdown (-0.17 kg [95% CI: -0.30 to -0.04]). Conclusion: Mitigating strategies to enforce the intervention and patient's follow-up during lockdown have been successful in preserving the integrity of the trial and ensuring its continuation, with minor effects on adiposity. Clinical trial registration: https://doi.org/10.1186/ISRCTN89898870, identifier ISRCTN89898870.

Impact of COVID-19 pandemic on the PREDIMED-Plus randomized clinical trial: Effects on the interventions, participants follow-up, and adiposity

Background The COVID-19 pandemic has affected the implementation of most ongoing clinical trials worldwide including the PREDIMED-Plus study. The PREDIMED-Plus is an ongoing, multicenter, controlled intervention trial, aimed at weight-loss and cardiovascular disease prevention, in which participants were randomized (1:1 ratio) to an intervention group (energy-reduced Mediterranean diet, promotion of physical activity, and behavioral support) or to a control group (Mediterranean diet with usual care advice). When the pandemic began, the trial was in the midst of the planned intervention. The objective of this report was to examine the effects of the pandemic on the delivery of the intervention and to describe the strategies established to mitigate the possible adverse effects of the pandemic lockdown on data collection and adiposity. Methods We assessed the integrity of the PREDIMED-Plus trial during 5 identified periods of the COVID-19 pandemic determined according to restrictions dictated by the Spanish government authorities. A standardized questionnaire was delivered to each of the 23 PREDIMED-Plus recruiting centers to collected data regarding the trial integrity. The effect of the restrictions on intervention components (diet, physical activity) was evaluated with data obtained in the three identified lockdown phases: pre lockdown, lockdown proper, and post lockdown. Results During the lockdown (March/2020-June/2021), 4,612 participants (48% women, mean age 65y) attended pre-specified yearly follow-up visits to receive lifestyle recommendations and obtain adiposity measures. The overall mean (SD) of the proportions reported by each center showed that 40.4% (25.4) participants had in-person visits, 39.8% (18.2) participants were contacted by telephone and 35% (26.3) by electronic means. Participants' follow-up and data collection rates increased across lockdown periods (from ≈10% at onset to ≈80% at the end). Compared to pre-lockdown, waist circumference increased during (0.75 cm [95% CI: 0.60–0.91]) and after (0.72 cm [95% CI: 0.56–0.89]) lockdown. Body weight did not change during lockdown (0.01 kg [95% CI: –0.10 to 0.13) and decreased after lockdown (-0.17 kg [95% CI: –0.30 to –0.04]). Conclusion Mitigating strategies to enforce the intervention and patient's follow-up during lockdown have been successful in preserving the integrity of the trial and ensuring its continuation, with minor effects on adiposity. Clinical trial registration https://doi.org/10.1186/ISRCTN89898870, identifier ISRCTN89898870.

Use of mobile phone sensing data to estimate residence and mobility times in urban patches during the COVID-19 epidemic: The case of the 2020 outbreak in Hermosillo, Mexico (preprint)

It is often necessary to introduce the main characteristics of population mobility dynamics to model critical social phenomena such as the economy, violence, transmission of information, or infectious diseases. In this work, we focus on modeling and inferring urban population mobility using the geospatial data of its inhabitants. The objective is to estimate mobility and times inhabitants spend in the areas of interest, such as zip codes and census geographical areas. The proposed method uses the Brownian bridge model for animal movement in ecology. We illustrate its possible applications using mobile phone GPS data in 2020 from the city of Hermosillo, Sonora, in Mexico. We incorporate the estimated residence-mobility matrix into a multi-patch compartmental SEIR model to assess the effect of mobility changes due to governmental interventions

At-home versus in-hospital initiation of non-invasive ventilation in obstructive sleep apnea patients

Introduction: The COVID-19 pandemic led to the development of numerous adaptations in the healthcare systems in order to minimize the risk of infection for patients and healthcare professionals. One of the main difficulties related to Sleep-related breathing disorders, namely Obstructive Sleep Apnea (OSA), was the initiation of noninvasive ventilation (NIV), as this procedure carries a high risk of transmission through aerosol generation. In our hospital, patients previously initiated NIV at the Sleep Disorders Clinic. However, due to the pandemic, this had to be suspended and NIV initiation began to take place at the patient's home. Our objective was to evaluate the difference in adherence to NIV when this therapy was initiated in-hospital or at home. Method(s): Retrospective study, evaluating the differences in NIV adherence between patients with OSA that initiated NIV in-hospital (previously to the pandemic) or at home (post-pandemic). Statistical analysis was performed using an independent samples t-test on SPSS Statistics version 27. Result(s): From the patients that had OSA diagnosed through polysomnography level 3, we selected 114, of which 60 initiated NIV inhospital and 54 initiated NIV at home. In both groups, the majority of patients were male (76,7% in the inhospital NIV initiation group and 70,4% in the home NIV initiation group), with a mean age of 60,9 +/- 10,4 years and 61,3 +/- 10,6 years, respectively. Most patients had severe OSAS (78,3% and 75,9%, respectively) and had a body mass index (BMI) >= 30 (76,6% and 81,5%, respectively). In the first-month post NIV initiation, mean adherence was 88,3% in patients that had in-hospital initiation and 85,0% in patients with home NIV initiation. In the sixth month was 89,2% and 85,9%, respectively, and after 1 year was 96,7% and 82,50%, respectively. No statistical difference was found between adherence in all periods (p > 0,05). Conclusion(s): Our work suggests that home initiation of NIV in OSAS patients has non-inferior results in terms of patients' adherence and is a possibility to maintain in the future. This will allow reallocation of human resources to other areas in Sleep Disorders that are understaffed.

Teclistamab in Relapsed or Refractory Multiple Myeloma.

BACKGROUND: Teclistamab is a T-cell-redirecting bispecific antibody that targets both CD3 expressed on the surface of T cells and B-cell maturation antigen expressed on the surface of myeloma cells. In the phase 1 dose-defining portion of the study, teclistamab showed promising efficacy in patients with relapsed or refractory multiple myeloma. METHODS: In this phase 1-2 study, we enrolled patients who had relapsed or refractory myeloma after at least three therapy lines, including triple-class exposure to an immunomodulatory drug, a proteasome inhibitor, and an anti-CD38 antibody. Patients received a weekly subcutaneous injection of teclistamab (at a dose of 1.5 mg per kilogram of body weight) after receiving step-up doses of 0.06 mg and 0.3 mg per kilogram. The primary end point was the overall response (partial response or better). RESULTS: Among 165 patients who received teclistamab, 77.6% had triple-class refractory disease (median, five previous therapy lines). With a median follow-up of 14.1 months, the overall response rate was 63.0%, with 65 patients (39.4%) having a complete response or better. A total of 44 patients (26.7%) were found to have no minimal residual disease (MRD); the MRD-negativity rate among the patients with a complete response or better was 46%. The median duration of response was 18.4 months (95% confidence interval [CI], 14.9 to not estimable). The median duration of progression-free survival was 11.3 months (95% CI, 8.8 to 17.1). Common adverse events included cytokine release syndrome (in 72.1% of the patients; grade 3, 0.6%; no grade 4), neutropenia (in 70.9%; grade 3 or 4, 64.2%), anemia (in 52.1%; grade 3 or 4, 37.0%), and thrombocytopenia (in 40.0%; grade 3 or 4, 21.2%). Infections were frequent (in 76.4%; grade 3 or 4, 44.8%). Neurotoxic events occurred in 24 patients (14.5%), including immune effector cell-associated neurotoxicity syndrome in 5 patients (3.0%; all grade 1 or 2). CONCLUSIONS: Teclistamab resulted in a high rate of deep and durable response in patients with triple-class-exposed relapsed or refractory multiple myeloma. Cytopenias and infections were common; toxic effects that were consistent with T-cell redirection were mostly grade 1 or 2. (Funded by Janssen Research and Development; MajesTEC-1 ClinicalTrials.gov numbers, NCT03145181 and NCT04557098.).

Genome-wide transcriptional profiling of pulmonary functional sequelae in ARDS- secondary to SARS-CoV-2 infection.

BACKGROUND: Up to 80% of patients surviving acute respiratory distress syndrome (ARDS) secondary to SARS-CoV-2 infection present persistent anomalies in pulmonary function after hospital discharge. There is a limited understanding of the mechanistic pathways linked to post-acute pulmonary sequelae. AIM: To identify the molecular underpinnings associated with severe lung diffusion involvement in survivors of SARS-CoV-2-induced ARDS. METHODS: Survivors attended to a complete pulmonary evaluation 3 months after hospital discharge. RNA sequencing (RNA-seq) was performed using Illumina technology in whole-blood samples from 50 patients with moderate to severe diffusion impairment (DLCO<60%) and age- and sex-matched individuals with mild-normal lung function (DLCO≥60%). A transcriptomic signature for optimal classification was constructed using random forest. Transcriptomic data were analyzed for biological pathway enrichment, cellular deconvolution, cell/tissue-specific gene expression and candidate drugs. RESULTS: RNA-seq identified 1357 differentially expressed transcripts. A model composed of 14 mRNAs allowed the optimal discrimination of survivors with severe diffusion impairment (AUC=0.979). Hallmarks of lung sequelae involved cell death signaling, cytoskeleton reorganization, cell growth and differentiation and the immune response. Resting natural killer (NK) cells were the most important immune cell subtype for the prediction of severe diffusion impairment. Components of the signature correlated with neutrophil, lymphocyte and monocyte counts. A variable expression profile of the transcripts was observed in lung cell subtypes and bodily tissues. One upregulated gene, TUBB4A, constitutes a target for FDA-approved drugs. CONCLUSIONS: This work defines the transcriptional programme associated with post-acute pulmonary sequelae and provides novel insights for targeted interventions and biomarker development.

Longitudinal Effects of Distress and Its Management During COVID-19 Lockdown in Spain.

Introduction: The COVID-19 pandemic that hit Spain during March 2020 forced the strict confinement of the population for 2 months. The objectives of this study were (a) to assess the magnitude and duration of the influence of confinement on people's Distress, (b) to study the temporal sequence of stress, and (c) to show how different day-to-day activities and personal variables influence perceived Distress levels. Method: A daily registration was completed by 123 people, with ages ranging from 21 to 75 years old ( X ¯ = 43, SD = 10 years), of which there were 40 men (32%) and 83 females (68%). During 45 days of lockdown, from March 19th to May 3rd, participants were asked to respond to a socio-demographic survey and make daily records comprising the MASQ-D30 and some day-to-day behaviors. Pooled time series was applied to establish what effect time had on the dependent variable. Results: Distress has a 14-day autoregressive function and gender, physical activity, sexual activity, listening to music, and teleworking also influence Distress. It has been hypothesized that the intercept presents variability at level 2 (individual), but it has not been significant. Interactions between Gender-Telecommuting, and Gender-Physical Activity were observed. Approximately 66% of the variance of Distress was explained (R 2 = 0.663). Discussion: At the beginning of the lockdown, the average levels of Distress were well above the levels of the end (z = 3.301). The individuals in the sample have followed a very similar process in the development of Distress. During the lockdown, the "memory" of Distress was 2 weeks. Our results indicate that levels of Distress depend on activities during lockdown. Interactions exist between gender and some behavioral variables that barely influence Distress in men but decrease Distress in women. The importance of routine maintenance and gender differences must be considered to propose future interventions during confinement.

Prognostic implications of comorbidity patterns in critically ill COVID-19 patients: A multicenter, observational study.

Background: The clinical heterogeneity of COVID-19 suggests the existence of different phenotypes with prognostic implications. We aimed to analyze comorbidity patterns in critically ill COVID-19 patients and assess their impact on in-hospital outcomes, response to treatment and sequelae. Methods: Multicenter prospective/retrospective observational study in intensive care units of 55 Spanish hospitals. 5866 PCR-confirmed COVID-19 patients had comorbidities recorded at hospital admission; clinical and biological parameters, in-hospital procedures and complications throughout the stay; and, clinical complications, persistent symptoms and sequelae at 3 and 6 months. Findings: Latent class analysis identified 3 phenotypes using training and test subcohorts: low-morbidity (n=3385; 58%), younger and with few comorbidities; high-morbidity (n=2074; 35%), with high comorbid burden; and renal-morbidity (n=407; 7%), with chronic kidney disease (CKD), high comorbidity burden and the worst oxygenation profile. Renal-morbidity and high-morbidity had more in-hospital complications and higher mortality risk than low-morbidity (adjusted HR (95% CI): 1.57 (1.34-1.84) and 1.16 (1.05-1.28), respectively). Corticosteroids, but not tocilizumab, were associated with lower mortality risk (HR (95% CI) 0.76 (0.63-0.93)), especially in renal-morbidity and high-morbidity. Renal-morbidity and high-morbidity showed the worst lung function throughout the follow-up, with renal-morbidity having the highest risk of infectious complications (6%), emergency visits (29%) or hospital readmissions (14%) at 6 months (p<0.01). Interpretation: Comorbidity-based phenotypes were identified and associated with different expression of in-hospital complications, mortality, treatment response, and sequelae, with CKD playing a major role. This could help clinicians in day-to-day decision making including the management of post-discharge COVID-19 sequelae. Funding: ISCIII, UNESPA, CIBERES, FEDER, ESF.

N-antigenemia detection by a rapid lateral flow test predicts 90-day mortality in COVID-19: A prospective cohort study.

OBJECTIVES: To evaluate if the detection of N antigen of SARS-CoV-2 in plasma by a rapid lateral flow test predicts 90-day mortality in COVID-19 patients hospitalized at the wards. METHODS: The presence of N-antigenemia was evaluated in the first 36 hours after hospitalization in 600 unvaccinated COVID-19 patients, by using the Panbio COVID-19 Ag Rapid Test Device from Abbott (Abbott Laboratories Inc., Chicago, IL, USA). The impact of N-antigenemia on 90-day mortality was assessed by multivariable Cox regression analysis. RESULTS: Prevalence of N-antigenemia at hospitalization was higher in nonsurvivors (69% (82/118) vs. 52% (250/482); p < 0.001). The patients with N-antigenemia showed more frequently RNAemia (45.7% (148/324) vs. 19.8% (51/257); p < 0.001), absence of anti-SARS-CoV-2 N antibodies (80.7% (264/327) vs. 26.6% (69/259); p < 0.001) and absence of S1 antibodies (73.4% (240/327) vs. 23.6% (61/259); p < 0.001). The patients with antigenemia showed more frequently acute respiratory distress syndrome (30.1% (100/332) vs. 18.7% (50/268); p = 0.001) and nosocomial infections (13.6% (45/331) vs. 7.9% (21/267); p = 0.026). N-antigenemia was a risk factor for increased 90-day mortality in the multivariable analysis (HR, 1.99 (95% CI,1.09-3.61), whereas the presence of anti-SARS-CoV-2 N-antibodies represented a protective factor (HR, 0.47 (95% CI, 0.26-0.85). DISCUSSION: The presence of N-antigenemia or the absence of anti-SARS-CoV-2 N-antibodies after hospitalization is associated to increased 90-day mortality in unvaccinated COVID-19 patients. Detection of N-antigenemia by using lateral flow tests is a quick, widely available tool that could contribute to early identify those COVID-19 patients at risk of deterioration.

Identification of circulating microRNA profiles associated with pulmonary function and radiologic features in survivors of SARS-CoV-2-induced ARDS.

There is a limited understanding of the pathophysiology of postacute pulmonary sequelae in severe COVID-19. The aim of current study was to define the circulating microRNA (miRNA) profiles associated with pulmonary function and radiologic features in survivors of SARS-CoV-2-induced ARDS. The study included patients who developed ARDS secondary to SARS-CoV-2 infection (n = 167) and a group of infected patients who did not develop ARDS (n = 33). Patients were evaluated 3 months after hospital discharge. The follow-up included a complete pulmonary evaluation and chest computed tomography. Plasma miRNA profiling was performed using RT-qPCR. Random forest was used to construct miRNA signatures associated with lung diffusing capacity for carbon monoxide (DLCO) and total severity score (TSS). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were conducted. DLCO < 80% predicted was observed in 81.8% of the patients. TSS showed a median [P25;P75] of 5 [2;8]. The miRNA model associated with DLCO comprised miR-17-5p, miR-27a-3p, miR-126-3p, miR-146a-5p and miR-495-3p. Concerning radiologic features, a miRNA signature composed by miR-9-5p, miR-21-5p, miR-24-3p and miR-221-3p correlated with TSS values. These associations were not observed in the non-ARDS group. KEGG pathway and GO enrichment analyses provided evidence of molecular mechanisms related not only to profibrotic or anti-inflammatory states but also to cell death, immune response, hypoxia, vascularization, coagulation and viral infection. In conclusion, diffusing capacity and radiological features in survivors from SARS-CoV-2-induced ARDS are associated with specific miRNA profiles. These findings provide novel insights into the possible molecular pathways underlying the pathogenesis of pulmonary sequelae.Trial registration: ClinicalTrials.gov identifier: NCT04457505..Trial registration: ISRCTN.org identifier: ISRCTN16865246..

Digital PCR applications for the diagnosis and management of infection in critical care medicine.

Infection (either community acquired or nosocomial) is a major cause of morbidity and mortality in critical care medicine. Sepsis is present in up to 30% of all ICU patients. A large fraction of sepsis cases is driven by severe community acquired pneumonia (sCAP), which incidence has dramatically increased during COVID-19 pandemics. A frequent complication of ICU patients is ventilator associated pneumonia (VAP), which affects 10-25% of all ventilated patients, and bloodstream infections (BSIs), affecting about 10% of patients. Management of these severe infections poses several challenges, including early diagnosis, severity stratification, prognosis assessment or treatment guidance. Digital PCR (dPCR) is a next-generation PCR method that offers a number of technical advantages to face these challenges: it is less affected than real time PCR by the presence of PCR inhibitors leading to higher sensitivity. In addition, dPCR offers high reproducibility, and provides absolute quantification without the need for a standard curve. In this article we reviewed the existing evidence on the applications of dPCR to the management of infection in critical care medicine. We included thirty-two articles involving critically ill patients. Twenty-three articles focused on the amplification of microbial genes: (1) four articles approached bacterial identification in blood or plasma; (2) one article used dPCR for fungal identification in blood; (3) another article focused on bacterial and fungal identification in other clinical samples; (4) three articles used dPCR for viral identification; (5) twelve articles quantified microbial burden by dPCR to assess severity, prognosis and treatment guidance; (6) two articles used dPCR to determine microbial ecology in ICU patients. The remaining nine articles used dPCR to profile host responses to infection, two of them for severity stratification in sepsis, four focused to improve diagnosis of this disease, one for detecting sCAP, one for detecting VAP, and finally one aimed to predict progression of COVID-19. This review evidences the potential of dPCR as a useful tool that could contribute to improve the detection and clinical management of infection in critical care medicine.

Bronchial Aspirate-Based Profiling Identifies MicroRNA Signatures Associated With COVID-19 and Fatal Disease in Critically Ill Patients.

BACKGROUND: The pathophysiology of COVID-19-related critical illness is not completely understood. Here, we analyzed the microRNA (miRNA) profile of bronchial aspirate (BAS) samples from COVID-19 and non-COVID-19 patients admitted to the ICU to identify prognostic biomarkers of fatal outcomes and to define molecular pathways involved in the disease and adverse events. METHODS: Two patient populations were included (n = 89): (i) a study population composed of critically ill COVID-19 and non-COVID-19 patients; (ii) a prospective study cohort composed of COVID-19 survivors and non-survivors among patients assisted by invasive mechanical ventilation (IMV). BAS samples were obtained by bronchoaspiration during the ICU stay. The miRNA profile was analyzed using RT-qPCR. Detailed biomarker and bioinformatics analyses were performed. RESULTS: The deregulation in five miRNA ratios (miR-122-5p/miR-199a-5p, miR-125a-5p/miR-133a-3p, miR-155-5p/miR-486-5p, miR-214-3p/miR-222-3p, and miR-221-3p/miR-27a-3p) was observed when COVID-19 and non-COVID-19 patients were compared. In addition, five miRNA ratios segregated between ICU survivors and nonsurvivors (miR-1-3p/miR-124-3p, miR-125b-5p/miR-34a-5p, miR-126-3p/miR-16-5p, miR-199a-5p/miR-9-5p, and miR-221-3p/miR-491-5p). Through multivariable analysis, we constructed a miRNA ratio-based prediction model for ICU mortality that optimized the best combination of miRNA ratios (miR-125b-5p/miR-34a-5p, miR-199a-5p/miR-9-5p, and miR-221-3p/miR-491-5p). The model (AUC 0.85) and the miR-199a-5p/miR-9-5p ratio (AUC 0.80) showed an optimal discrimination value and outperformed the best clinical predictor for ICU mortality (days from first symptoms to IMV initiation, AUC 0.73). The survival analysis confirmed the usefulness of the miRNA ratio model and the individual ratio to identify patients at high risk of fatal outcomes following IMV initiation. Functional enrichment analyses identified pathological mechanisms implicated in fibrosis, coagulation, viral infections, immune responses and inflammation. CONCLUSIONS: COVID-19 induces a specific miRNA signature in BAS from critically ill patients. In addition, specific miRNA ratios in BAS samples hold individual and collective potential to improve risk-based patient stratification following IMV initiation in COVID-19-related critical illness. The biological role of the host miRNA profiles may allow a better understanding of the different pathological axes of the disease.